EE225B, Spring 2018
Digital Image Processing
Tue. and Thu.: 09:30  11:00 am
540 Cory
Prerequisite: EE120
Required Text:

R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice Hall, 4th Edition.
Video lectures:
EE225B, Spring 2018
Course Details:

Lecturer:
Professor Avideh Zakhor
avz@eecs.berkeley.edu
507 Cory Hall
Phone: (510) 6436777
Office Hours:
Thursday 11:00am  12:00pm in 507 Cory
TA:
Xinlei Pan
xinleipan@berkeley.edu
Office Hours:
Monday 45 pm, location: Cory 504; Friday 45 pm, location: Soda 510 VCL.

Recommended Texts:

Bovik, Handbook of Image and Video Processing, Academic Press 2000.

N. Netravali and Barry G. Haskell, Digital Pictures, Plenum Press, 1988.
 W.K.Pratt, Digital Image Processing, John Wiley and Sons, 1992.
 A.M. Tekalp, Digital Video Processing, Prentice Hall, 1995.
Other useful references:

D. E. Dudgeon and R. M. Mersereau, MultiDimensional Digital Signal Processing, Prentice Hall, 1984.

V. Oppenheim and R. W. Schafer, Digital Signal Processing, PrenticeHall, 1975.

T. S. Huang, editor, TwoDimensional Digital Signal Processing, Topics in Applied Physics, vol. 42 and vol. 43, SpringerVerlag, 1981.

S. K. Mitra and M. P. Ekstrom, editors, TwoDimensional Digital Signal Processing, Dowden, Hutchison, and Ross, 1978.

R. C. Gonzalez and P. Wintz, Digital Image Processing, AddisonWesley, 1979.

H. C. Andrews and B. R. Hunt, Digital Image Restoration, PrenticeHall, 1977.

H. C. Andrews, Tutorial and Selected Papers in Digital Image Processing, IEEE Press, 1978.

W. F. Schrieber, Fundamentals of Electronic Imaging Systems, SpringerVerlag, 1986.

K. Jain, Fundamentals of Digital Image Processing, Prentice Hall, 1989.
Outline of Topics:

Image sensing and acquisition, sampling, quantization

Spatial transformations, filtering in space domain and frequency domain.

Image restoration, enhancement, reconstruction; computed tomography

Wavelets and multiresolution processing

Image and video compression and communication; watermarking

Morphological Image processing

Color processing

Edge detection; feature extraction; SIFT, MSER

Image segmentation

Neural networks and deep learning

3D image processing

Applications to augmented reality and virtual reality
Homework:
Homework will be issued approximately once every one or two weeks. They will either consist of written assignments, Matlab assignments or C programming assignments. Homework will be graded, and will contribute 55% to the final grade. Homework handed in late will not be accepted unless consent is obtained from the teaching staff prior to the due date. There will be a project that will constitute 35% of your grade. The project can be individual or in a group. You are to submit a proposal to the instructor by the end of March. More details on the project will be provided later, and a list of suggested topics will be provided. In addition, 10% of your grade will be for in class participation.


Welcome to EE225B!

01/19/18: Instructions on how to get matlab are here.

01/30/18: Extra office hour this week: 02/02/18 Fri 45 pm at Cory 504.
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 Lecture 1: Introduction.
Tues., Jan. 16, 2018
 Lecture 2: Fundamentals: electromagnetic spectrum
Thurs., Jan. 18, 2018
 Lecture 3: Sensing: sampling; quantization
Tues., Jan. 23, 2018
 Lecture 4: Sensing: sampling; quantization
Thurs., Jan 25, 2018
 Lecture 5: Sensing: sampling; quantization
Tues., Jan 30, 2018
 Lecture 6: Intensity Transformation and Spatial Filtering
Thurs., Feb 1, 2018
 Lecture 7: enhacement_picture_lim
Tues., Feb 6, 2018
 Lecture 8: Filtering in the Frequency Domain
Thurs., Feb 8, 2018
 Lecture 9: Image Restoration
Thurs., Feb 13, 2018.
 Lecture 10: Tomography
Thurs., Mar 8, 2018.
 Lecture 11: Image Quantization and Bit Allocation
Thurs., Mar 13, 2018.
 Lecture 12: Transform Image Coding
Thurs., Mar 15, 2018.
 Lecture 13: JPEG2000, Pyramid, Wavelets, wavelet_numbai.
Thurs., Mar 22, 2018.
 Lecture 14: Multiresolution Analysis.
Thurs., April 5, 2018.
 Lecture 15: Short Term Fourier Transform and Wavelets.
Tues., April 10, 2018.
 Lecture 16: Motion Estimation
Thurs., April 12, 2018.
 Lecture 17: Image Reconstruction from Partial Fourier Information.
Reconstruction from Fourier Transform Phase , Signal Reconstruction from Level Crossing
Tues., April 17, 2018.
 Lecture 18: Video Standards.
Thurs., April 19, 2018.

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 Week 2(1/221/26): Read Chapters 1 and 2 of Gonzalez and Woods
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Submit files to
ee225b2018sp@gmail.com

Homework 1
Download the image for Homework 1 from the book web page.
Problem 2 is here, Problem 3 is here
Due by 9: 00 a.m. on Thur. Feb. 8th, 2018.
Solution is here

Homework 2
Project 33 is here, Project 37 is here, Project 38, 39 is here
Download checkerboard1024shaded.tif,
hiddenhorse.tif,
spillwaydark.tif,
testpattern1024.tif,
expected results for project 3.7 (c) is hereandhere
Due by 9: 00 a.m. on Tues, Feb. 20, 2018.
Solutions are here.

Homework 3.
Please refer to the image restoration tutorial for further information.
Due by 9: 00 a.m. on Tues. March 6, 2018.
Solutions are here.
NoisyImg.bmp, NoisyBlur.bmp

Homework 4.
Pyramid.bmp.
Solution.
Due by 9: 00 a.m. on Thur., March 22, 2018.

Homework 5. Images Compression.
Solution.
Due by 9: 00 a.m. on Tues., April 03, 2018.

Homework 6. Wavelets.
Solution
Due by 9: 00 a.m. on Tues., April 10, 2018.

Homework 7, Phase.dat, Magnitude.dat, Test.bmp
Due by 9: 00 a.m. on Tues., April 24, 2018.
Solution.
Signals, Systems and Fourier Transform
MultiDimensional Fourier Transform
Image Restoration
Embedded Image Coding Using Zerotrees of Wavelets Coefficients
Review of Algorithms for Reconstruction of images from Fourier Transform Magnitude
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